A multiomics disease progression signature of low-risk ccRCC
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PROVIDER: PRJNA856166 | ENA |
REPOSITORIES: ENA
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Project description:Background: Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer. Identification of ccRCC likely to progress, despite an apparent low risk at the time of surgery, represents a key clinical issue. Methods: From a cohort of adult ccRCC patients (n=443), we selected low-risk tumors progressing within a 5-years average follow-up (progressors: P, n=8) and non-progressing (NP) tumors (n=16). Transcriptome sequencing, miRNA sequencing and proteomics were performed on tissues obtained at surgery. Our work suggests that LXR, FXR and macrophage activation pathways could be critically involved in the inhibition of the progression of low-risk ccRCC. Furthermore, a 10-component classifier could support an early identification of apparently low-risk ccRCC patients.
2022-08-10 | GSE207557 | GEO
Project description:Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer. Identification of ccRCC likely to progress, despite an apparent low risk at the time of surgery, represents a key clinical issue. From a cohort of adult ccRCC patients (n = 443), we selected low-risk tumors progressing within a 5-years average follow-up (progressors: P, n = 8) and non-progressing (NP) tumors (n = 16). Transcriptome sequencing, miRNA sequencing and proteomics were performed on tissues obtained at surgery. We identified 151 proteins, 1167 mRNAs and 63 miRNAs differentially expressed in P compared to NP low-risk tumors. Pathway analysis demonstrated overrepresentation of proteins related to "LXR/RXR and FXR/RXR Activation", "Acute Phase Response Signaling" in NP compared to P samples. Integrating mRNA, miRNA and proteomic data, we developed a 10-component classifier including two proteins, three genes and five miRNAs, effectively differentiating P and NP ccRCC and capturing underlying biological differences, potentially useful to identify "low-risk" patients requiring closer surveillance and treatment adjustments. Key results were validated by immunohistochemistry, qPCR and data from publicly available databases. Our work suggests that LXR, FXR and macrophage activation pathways could be critically involved in the inhibition of the progression of low-risk ccRCC. Furthermore, a 10-component classifier could support an early identification of apparently low-risk ccRCC patients.
| S-EPMC9356046 | biostudies-literature
Project description:Patients with polycystic kidney disease (PKD) encounter a high risk of clear cell renal cell carcinoma (ccRCC), a malignant tumor with dysregulated lipid metabolism. SET domain–containing 2 (SETD2) has been identified as an important tumor suppressor gene in ccRCC. However, the role of SETD2 in tumorigenesis during the transition from PKD to ccRCC remains largely unexplored. Herein, we performed metabolomics, lipidomics, transcriptomics and proteomics with SETD2 loss induced PKD-ccRCC transition mouse model. To characterize biological responses triggered by SETD2 deletion during PKD-ccRCC transition at the protein level, we conducted global proteomics studies.
2023-10-31 | PXD038966 | Pride
Project description:Background. Current clinicopathological factors are not accurate enough to predict tumor progression in intermediate/high-risk clear cell renal cell carcinoma (ccRCC). Objective: To develop a prognostic classifier for intermediate/high-risk ccRCC based on gene expression and histopathological prognostic factors. Design, setting and participants: Retrospective, multicenter study including 84 intermediate/high-risk ccRCC patients who underwent surgery. Global gene expression patterns were analyzed in 13 tissue samples from progressive and non-progressive ccRCC using Illumina Hi-seq 2000 kit. Expression levels of 22 selected genes were assessed by nCounter Analysis in an independent series of 71 ccRCC. A combined genetic-clinicopathological classifier for predicting tumor progression was developed. Outcomes measurements and statistical analysis: Logistic regression analysis was used to identify independent prognostic factors. Results and Limitations: A total of 1202 genes were found differentially expressed between progressive and non-progressive intermediate/high-risk ccRCC. In the independent cohort, 7 genes remained significant differentially expressed between the groups. Expression of HS6ST2, pT stage, tumor size and ISUP grade were found independent prognostic factors for tumor progression (p<0.05). A risk score generated using these variables was able to distinguish a subset of patients at higher-risk of progression (HR 7,27; p<0,001), improving the individual discriminative performance of each of these variables on their own. Conclusions: A novel prognostic algorithm based on genetic and clinicopathological factors was successfully developed. This model may aid physicians to select high-risk patients for further adjuvant target therapy or immune therapy.
2021-12-29 | GSE175648 | GEO
Project description:The molecular profile of endometrial cancer has become an important tool in determining patient prognosis and their optimal adjuvant treatment. In addition to The Cancer Genome Atlas (TCGA), simpler tools have been developed, such as the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE). We attempted to determine a genetic signature to build a recurrence risk score in patients diagnosed with low- and intermediate-risk endometrial cancer. A case-control study was conducted. The eligible patients were women diagnosed with recurrence low- and intermediate-risk endometrial cancer between January 2009 and December 2014 at a single institution; the recurrence patients were matched to two nonrecurrence patients with the same diagnosis by age and surgical staging. Following RNA isolation of 51 cases, 17 recurrence and 34 nonrecurrence patients, the expression profile was determined using the nCounter® PanCancer Pathways Panel, which contains 770 genes. The expression profile was successfully characterized in 49/51 (96.1%) cases. We identified 12 genes differentially expressed between the recurrence and nonrecurrence groups. The ROC curve for each gene was generated, and all had AUCs higher than 0.7. After backward stepwise logistic regression, four genes were highlighted: FN1, DUSP4, LEF1, and SMAD9. The recurrence risk score was calculated, leading to a ROC curve of the 4-gene model with an AUC of 0.93, sensitivity of 100%, and specificity of 72.7%. We identified a four-gene signature that is associated the risk of recurrence in patients with low- and intermediate-risk endometrial cancer. This finding suggests a new prognostic factor in this poorly explored group of patients with endometrial cancer.
2021-07-27 | GSE178671 | GEO
Project description:A 4-gene signature associated with recurrence risk in patients with low and intermediate-risk endometrial cancer
| PRJNA739987 | ENA
Project description:Local and systemic multiomics signature of eosinophilic esophagitis (EO) in children
| PRJNA763516 | ENA
Project description:Based on multiple public databases, we investigated the expression level of BGN in ccRCC, its clinical significance, and its association with immune cells. Real-time fluorescence quantitative PCR was employed to validate BGN expression in tumor and adjacent normal tissues. Differential gene analysis, GO-KEGG analysis, and GSEA analysis were performed by RNA sequencing to elucidate the underlying signaling pathways. BGN knockdown cells were generated through lentiviral transfection to examine the impact of BGN on ccRCC. Cell proliferation, migration, and invasion were assessed using CCK8, colony formation, wound healing, Transwell migration, and invasion assays, respectively. Results: Our findings from database analysis and polymerase chain reaction (PCR) revealed a significant upregulation of BGN expression in kidney cancer tissues compared to normal tissues. Further analysis demonstrated a correlation between high BGN expression and ccRCC progression and immune infiltration. In vitro experiments confirmed that BGN silencing effectively inhibited cell proliferation, migration, and invasion of ccRCC. Mechanistically, these effects may be mediated through the MAPK signaling pathway. Conclusion: BGN potentially plays a pivotal role in the progression and metastasis of ccRCC, possibly acting through the MAPK signaling pathway. Therefore, BGN holds promise as a potential therapeutic target for ccRCC.
2024-09-01 | GSE264075 | GEO
Project description:Purpose: Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer. Thirty percent of patients with localized ccRCC develop metastases during follow-up. Although current scoring methods correctly identify patients at low progression risk, a small subgroup still experiences metastatization. We therefore aimed to identify ccRCC progression biomarkers in “low-risk” patients, potentially eligible for adjuvant treatments. Methods: We performed next-generation sequencing of RNA from formalin-fixed samples obtained at initial surgery from 8 “low-risk” patients with progressing tumours and 16 patients with similar Leibovich score, tumour stage and size, creatinine levels and surgical treatment, not progressing to recurrence with metastasis. Key results were confirmed with qPCR, immunohistochemistry and in external data. Results: Principal component analysis indicates that systematic transcriptomic differences are detectable at the time of initial surgery. 1167 genes, related to cancer and immune-related pathways, were differentially expressed between progressors and non-progressors. Search for a classifier revealed that overexpression of AGAP2-AS1, an antisense long non-coding RNA, alone, correctly classified 23 of 24 samples without requiring larger gene panels. AGAP2-AS1 gene overexpression was confirmed by qPCR (p <0.05) and correlated with shorter progression-free survival (p: <0.0005). Immunohistochemistry confirmed upregulation at the protein level of AGAP2. Conclusion: AGAP2-AS1 may represent a novel biomarker identifying high risk patients currently classified as “low risk” at the time of surgery.
2021-12-29 | GSE171955 | GEO
Project description:To identify a therapeutic candidate target molecule for ccRCC, we analyzed the microRNA (miRNA) expression signatures in ccRCC clinical specimens. 9 matched pair (normal tissue and ccRCC tissue) plus 7 ccRCC tissue were analyzed for miRNA-microarray
2014-02-20 | E-GEOD-55138 | biostudies-arrayexpress